
\begin{landscape}\begin{table}[!h]
\centering
\caption{Government Framing of Diaspora with Racism and Violence by Standard Error Type\label{tab:ethnicse}}
\centering
\resizebox{\ifdim\width>\linewidth\linewidth\else\width\fi}{!}{
\begin{threeparttable}
\begin{tabular}[t]{lllllllllll}
\toprule
\multicolumn{1}{c}{\em{ }} & \multicolumn{10}{c}{\em{Similarity with Diaspora Dictionary (\%)}} \\
\multicolumn{1}{c}{ } & \multicolumn{5}{c}{Racism} & \multicolumn{5}{c}{Violence} \\
\cmidrule(l{3pt}r{3pt}){2-6} \cmidrule(l{3pt}r{3pt}){7-11}
  & Hetero. (1) & Cluster (Obj) (2) & Boot (Obj) (3) & Cluster (Attr) (4) & Boot (Attr) (5) & Hetero. (6) & Cluster (Obj) (7) & Boot (Obj) (8) & Cluster (Attr) (9) & Boot (Attr) (10)\\
\midrule
Government & 3.64*** & 3.64** & 3.64*** & 3.64*** & 3.64*** & 1.83*** & 1.83*** & 1.83*** & 1.83** & 1.83**\\
 & (0.91) & (1.43) & (1.23) & (0.87) & (0.76) & (0.45) & (0.56) & (0.48) & (0.77) & (0.73)\\
ln Frequency 1 & -2.82*** & -2.82*** & -2.82*** & -2.82*** & -2.82*** & -3.29*** & -3.29*** & -3.29*** & -3.29*** & -3.29***\\
 & (0.45) & (1.08) & (0.92) & (0.41) & (0.39) & (0.25) & (0.47) & (0.42) & (0.24) & (0.23)\\
ln Frequency 2 & -1.18*** & -1.18 & -1.18 & -1.18*** & -1.18*** & -1.96*** & -1.96*** & -1.96*** & -1.96*** & -1.96***\\
 & (0.43) & (0.88) & (0.78) & (0.25) & (0.23) & (0.23) & (0.36) & (0.32) & (0.37) & (0.35)\\
\midrule
\addlinespace[]
\multicolumn{11}{l}{\textit{Statistics}}\\
\hspace{1em}Observations & 489 & 489 & 489 & 489 & 489 & 963 & 963 & 963 & 963 & 963\\
\addlinespace[]
\multicolumn{11}{l}{\textit{Fixed effects}}\\
\hspace{1em}Dictionary FE & Yes & Yes & Yes & Yes & Yes & Yes & Yes & Yes & Yes & Yes\\
\bottomrule
\end{tabular}
\begin{tablenotes}
\item Notes: $^{*}$p$<$0.1; $^{**}$p$<$0.05; $^{***}$p$<$0.01 Regressions labeled with ``Boot" use Wild Bootstrapping to compute standard errors. Dependent variable is cosine similarity between respective object and attribute dictionaries. Controls for dictionary frequency are shown. Unit of analysis is the object-attribute word pair, which varies according to the object and attribute dictionary size.
\end{tablenotes}
\end{threeparttable}}
\end{table}
\end{landscape}
